Computational Modeling Center

Providing solutions at every scale . . .

We provide problem solving services and consulting on the use of applied mathematical and computational techniques to improve decision making, research, and planning efforts in the business and technology areas.

We bring state-of-the-art solutions to research and engineering problems using . . .

Computational Chemistry: To efficiently design, develop, and improve materials sometimes requires knowledge of the properties of those materials before they have ever been made. Where does this knowledge come from? From the fundamental sciences that describe the ways that all materials behave: quantum, classical, and statistical mechanics. Our computational chemistry and materials group applies these sciences via high performance computing to produce predictions of materials' performance attributes, engineering properties, safety characteristics, and their costs.

Computational Fluid Dynamics: CFD technologies allow engineers and scientists to predict fluid flow, heat and mass transfer, chemical reactions and related phenomena. By solving fundamental equations governing the transport processes, a CFD analysis provides information on important characteristics such as pressure loss, flow distribution and mixing efficiency. CFD analyses are used for early conceptual studies of new designs, detailed product development, scale-up, troubleshooting and system retrofitting.

Applied Mathematics and Numerical Methods: Applied mathematics and scientific computing are pervasive within the Computational Modeling Center. Our emphasis is on developing and applying mathematics and the elements of scientific computing to new ‘problems’ for which solutions either do not exist or are not in a convenient form.

Kinetics and Reactor Modeling: Air Products is continuously involved in the development of new products and advanced materials. These are manufactured using a wide variety of chemicals in a broad range of reactors, some operated in continuous mode and others operated in batch or semi-batch mode. Fundamentals of reactions and its interactions with transport processes in a reactor are key to the design and scale-up of the chemical processes.

Process Modeling and Optimization: Process Modeling is the art and science of representing processes (e.g. technical, econometric, work-process) through mathematical relationships involving equations, variables, and parameters, such that the system of equations can be solved either analytically or through application of appropriate numerical methods. These relationships are then utilized in an optimization framework to achieve desirable performance objectives (e.g. cost, process efficiency, material properties etc.) within the practical constraints of the system. Statistical Sciences: Statistical techniques are extensively utilized in operations, scientific and engineering work. Through methodologies such as design of experiments (DOE), equipment reliability analysis, statistical quality and process control, regression analysis, calibration, method detection limits, manufacturing operational improvements; statistical techniques facilitate modeling, analysis and optimization of laboratory, pilot and commercial plant operations. In recent years, image analysis is used to statistically obtain process measures or models from optical data which can be used to optimize processes.

Data Mining: Data mining techniques for exploring and analysis of large quantities of data are becoming very popular. These methodologies allow us to build key insights about our processes and systems by uncovering hidden correlations, and statistically significant patterns. These techniques are being applied in optimization of plant operations as well as to facilitate decision-making associated with business forecasting, sales and marketing.

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Providing solutions at every scale . . .

We provide problem solving services and consulting on the use of applied mathematical and computational techniques to improve decision making, research, and planning efforts in the business and technology areas.

We bring state-of-the-art solutions to research and engineering problems using . . .

Computational Chemistry: To efficiently design, develop, and improve materials sometimes requires knowledge of the properties of those materials before they have ever been made. Where does this knowledge come from? From the fundamental sciences that describe the ways that all materials behave: quantum, classical, and statistical mechanics. Our computational chemistry and materials group applies these sciences via high performance computing to produce predictions of materials' performance attributes, engineering properties, safety characteristics, and their costs.

Computational Fluid Dynamics: CFD technologies allow engineers and scientists to predict fluid flow, heat and mass transfer, chemical reactions and related phenomena. By solving fundamental equations governing the transport processes, a CFD analysis provides information on important characteristics such as pressure loss, flow distribution and mixing efficiency. CFD analyses are used for early conceptual studies of new designs, detailed product development, scale-up, troubleshooting and system retrofitting.

Applied Mathematics and Numerical Methods: Applied mathematics and scientific computing are pervasive within the Computational Modeling Center. Our emphasis is on developing and applying mathematics and the elements of scientific computing to new ‘problems’ for which solutions either do not exist or are not in a convenient form.

Kinetics and Reactor Modeling: Air Products is continuously involved in the development of new products and advanced materials. These are manufactured using a wide variety of chemicals in a broad range of reactors, some operated in continuous mode and others operated in batch or semi-batch mode. Fundamentals of reactions and its interactions with transport processes in a reactor are key to the design and scale-up of the chemical processes.

Process Modeling and Optimization: Process Modeling is the art and science of representing processes (e.g. technical, econometric, work-process) through mathematical relationships involving equations, variables, and parameters, such that the system of equations can be solved either analytically or through application of appropriate numerical methods. These relationships are then utilized in an optimization framework to achieve desirable performance objectives (e.g. cost, process efficiency, material properties etc.) within the practical constraints of the system. Statistical Sciences: Statistical techniques are extensively utilized in operations, scientific and engineering work. Through methodologies such as design of experiments (DOE), equipment reliability analysis, statistical quality and process control, regression analysis, calibration, method detection limits, manufacturing operational improvements; statistical techniques facilitate modeling, analysis and optimization of laboratory, pilot and commercial plant operations. In recent years, image analysis is used to statistically obtain process measures or models from optical data which can be used to optimize processes.

Data Mining: Data mining techniques for exploring and analysis of large quantities of data are becoming very popular. These methodologies allow us to build key insights about our processes and systems by uncovering hidden correlations, and statistically significant patterns. These techniques are being applied in optimization of plant operations as well as to facilitate decision-making associated with business forecasting, sales and marketing.

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